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Cardossier MCP Server

Cardossier MCP Server

by Joyall-au
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_regional_pricing

Compare average car prices across Polish regions against the national average to spot regional price differences.

Instructions

Compare average prices across Polish voivodeships vs. the national average. Costs 8 credits per call; failed calls are auto-refunded.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "make": "<make>",
      "model": "<model>",
      "year": "<year>"
    },
    "name": "get_regional_pricing"
  }
}

Input Schema

NameRequiredDescriptionDefault
makeYes
yearYes
modelYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

This description discloses a credit cost of 8 credits per call and auto-refund on failed calls, adding useful operational context beyond the schema. Since no annotations are provided, this cost and refund behavior is valuable, though it does not explain other behaviors like rate limits or data freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is just two sentences: the first front-loads the core purpose, and the second adds the cost/refund detail. No unnecessary words or repetition of schema information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has an output schema, so return values need not be described, and the cost/refund info adds operational context. However, the lack of parameter semantics and the absence of any usage guidance leave gaps in completeness for a tool with three required inputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage for its three parameters (make, model, year). The description does not elaborate on what these parameters mean or how they relate to the pricing comparison, leaving the agent to infer their purpose from the tool name alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool compares average prices across Polish voivodeships vs. the national average. The verb 'compare' and specific geographic scope distinguish it from siblings like get_price_history or get_market_valuation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when regional price comparison is needed) but does not explicitly mention when not to use it or contrast it with sibling tools. There is no exclusionary guidance or alternative tool references.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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